Abstract: A method includes training a first machine learning model with a first dataset, to produce a first trained machine learning model to infer cybersecurity-oriented file properties and/or detect cybersecurity threats within a first domain. The first dataset includes labeled files associated with the first domain. The first trained machine learning model includes multiple layers, some of which are trainable. A second trained machine learning model is generated, via a transfer learning process, using (1) at least one trainable layer from the multiple trainable layers of the first trained machine learning model, and (2) a second dataset different from the first dataset. The second dataset includes labeled files associated with a second domain. The first domain has a different syntax, different semantics, and/or a different structure than that of the second domain. The second trained machine learning model (e.g.

Abstract: Implementations relate to determining whether and/or how to implement a user request to prevent a particular search result from being provided in response to a search query. Some of those implementations grant or deny the request based on processing of the particular search result, the search query, and/or account information for a user submitting the user request. For example, some implementations process such information utilizing a classifier in determining whether to automatically deny the request, automatically approve the request, or to provide the request for manual review. Some additional or alternative implementations at least selectively automatically expand (or suggest for automatic expansion) an approval of a request to search result(s) and/or to one or more search queries that are not specified in the request.

Abstract: A user can submit a visual query that includes one or more images. Various processing techniques such as optical character recognition (OCR) techniques can be used to recognize text (e.g. in the image, surrounding image(s), etc.) and/or various object detection techniques (e.g., machine-learned object detection models, etc.) may be used to detect objects (e.g., products, landmarks, animals, humans, etc.) within or related to the visual query. Content related to the detected text or object(s) can be identified and potentially provided to a user as search results or a proactive content feed. As such, aspects of the present disclosure enable the visual search system to more intelligently process a visual query to provide improved search results and content feeds, including those search results which are more personalized and/or consider contextual signals to account for implicit characteristics of the visual query and/or user's search intent.

Abstract: A system includes a light source to generate a source light, a spatial modulator to receive the source light. A display element to receive the source light from the spatial modulator and to direct the source light towards an eye, and a controller. The controller is to receive initial image data for an image to be displayed, the image comprising a plurality of pixels having a plurality of brightness levels, determine an image power based on the brightness levels, and determine an excess power status based on a comparison of the image power to a specified power threshold. Responsive to the excess power status indicating the image power is to exceed the specified power threshold, the controller is to reduce the brightness levels to generate updated image data, and control the light source and the spatial modulator to project the image using the updated image data.

Abstract: Implementations include actions of obtaining a set of entities based on one or more terms of a query, obtaining one or more entities associated with each live event of a plurality of live events, identifying a live event that is responsive to the query based on comparing at least one entity in the set of entities to one or more entities associated with each live event of a plurality of live events, determining that an event search result corresponding to the live event is to be displayed in search results, and in response: providing the event search result for display, the event search result including information associated with the live event, the information including an indicator of an occurrence of the live event.

Abstract: Implementations set forth relate to suggesting an alternate interface modality when an automated assistant and/or a user is expected to not understand a particular interaction between the user and the automated assistant. In some instances, the automated assistant can pre-emptively determine that a forthcoming and/or ongoing interaction between a user and an automated assistant may experience interference. Based on this determination, the automated assistant can provide an indication that the interaction may not be successful and/or that the user should interact with the automated assistant through a different modality. For example, the automated assistant can render a keyboard interface at a portable computing device when the automated assistant determines that an audio interface of the portable computing device is experiencing interference.

Abstract: Systems and methods related to simulated light-in-flight imaging are described. A computing device may execute a light-in-flight engine to process an optical image and a corresponding depth map to produce a light-in-flight image or video that simulates propagation of a wavefront across a scene. The light-in-flight engine may generate an optical simulation output by transforming a depth map to a three-dimensional lift domain to produce a three-dimensional data structure, then convolving the three-dimensional data structure with a convolutional operator, which may define a Gaussian sphere, to produce a filtered three-dimensional data structure. The light-in-flight engine then affine transforms the optical image with an identified slice of the filtered three-dimensional data structure to produce a light-in-flight image.

Abstract: A system includes a server to generate a real-time stream of audio packets and a client device to decode and playback the audio content of the stream. The client device includes a network interface configured to receive a stream of audio packets via a network and a buffer configured to temporarily buffer a subset of audio packets of the stream. The client device further includes an audio decoder having an input to receive audio packets from the buffer and an output to provide corresponding segments of a decoded audio data stream. The client device also includes a stream monitoring module configured to provide an audio packet of the subset in the buffer which was previously decoded by the decoder to the input of the decoder again for a repeated decoding in place of a decoding of an audio packet that is lost or late.

Abstract: Provided are methods, systems, devices, apparatuses, and tangible non-transitory computer readable media for navigation and geocoding. The disclosed technology can perform operations including accessing location data and semantic tags. The location data can include information associated with locations including the location of a carrier and the location of a passenger. The semantic tags can include information associated with features of the locations. The location data and the semantic tags that satisfy meeting criteria can be identified. The meeting criteria can be associated with a suitability of a location for the carrier and the passenger. A meeting location for the carrier and the passenger can be determined based on the location data and the semantic tags that satisfy the meeting criteria. Furthermore, indications associated with the meeting location can be generated based on the features of the meeting location.

Abstract: Systems and methods of parallel uniform resource identifier resource extraction are provided. A tracking uniform resource identifier (URI) generation component can generate a first uniform resource locator (URL) that, responsive to actuation by a client computing device, causes the client computing device to send a content item identifier of a content item and a device identifier of the client computing device, via a computer network, to a records server at a first network location identified by the first URL. A resource URI generation component can generate a second URL that, responsive to actuation by the client computing device, causes the client computing device to retrieve, via the computer network, a first resource from a second network location identified by the second URL for display by the client computing device. A content item packaging component can generate the content item.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for index-side synonym expansion. One method includes obtaining a token sequence for a resource and indexing a token in the token sequence. The indexing includes applying one or more stemming rules to the particular token to generate a stemmed form of the token, obtaining a variant of the stemmed form of the token, and storing data associating the resource with both the token and the variant as index terms for the resource in a search engine index.

Abstract: System and methods are provided for generating panoramic imagery. An example method may be performed by one or more processors and includes obtaining first panoramic imagery depicting a geographic area. The method also includes obtaining an image depicting one or more physical objects absent from the first panoramic imagery. Further, the method includes transforming the first panoramic imagery into second panoramic imagery depicting the one or more physical objects and including at least a portion of the first panoramic imagery.

Abstract: Transform kernel candidates including a vertical transform type associated with a vertical motion and a horizontal transform type associated with a horizontal motion can be encoded or decoded. During a decoding operation, a probability model for decoding encoded bitstream video data associated with a transform kernel candidate for an encoded transform block is identified based on one or both of a first transform kernel candidate selected for an above neighbor transform block of the encoded transform block or a second transform kernel candidate selected for a left neighbor transform block of the encoded transform block. The encoded bitstream video data associated with the transform kernel candidate is decoded using the probability model.

Abstract: A computer-implemented method can include receiving, by a computing system including one or more computing devices, data describing a media content item that includes a plurality of image frames for sequential display. The method can include inputting, by the computing system, the data describing the media content item into a machine-learned temporal analysis model that is configured to receive the data describing the media content item, and in response to receiving the data describing the media content item, output temporal analysis data that describes temporal information associated with sequentially viewing the plurality of image frames of the media content item. The method can include receiving, by the computing system and as an output of the machine-learned temporal analysis model, the temporal analysis data.

Abstract: A method includes adding, by a first computing device, a first audio watermark to first speech data corresponding to playback of a first utterance including a hotword used to invoke an attention of a second computing device. The method includes outputting, by the first computing device, the playback of the first utterance corresponding to the watermarked first speech data. The second computing device is configured to receive the watermarked first speech data and determine to cease processing of the watermarked first speech data.

Abstract: One or more processors, operating in a source base station and/or a target base station, determines a change in the termination point from the source base station to the target base station for a radio bearer with a current count value according to data unit sequencing. The one or more processors determine (1806) whether a user equipment (UE) changes the data unit sequencing as a result of the change in the termination point. In a first instance, the one or more processors cause the target base station to apply (1810) the current count value to the radio bearer, in response to determining that the data unit sequencing does not change. In a second instance, the one or more processors cause the target base station to apply (1820) a new count value different from the current count value to the radio bearer, in response to determining that the data unit sequencing changes.

Abstract: To provide context-aware audio navigation instructions, a server device obtains sets of audio navigation instructions previously provided to users along with sensor data descriptive of a context in which the audio navigation instructions were provided and an indication of whether a driver correctly responded to the audio navigation instructions. The server device trains a machine learning model using this data, where the machine learning model identifies audio navigation instruction parameters for a particular context. In response to a request for navigation directions, the server device receives sensor data from the client computing device generating the request that is indicative of the environment surrounding the client computing device. The server device then applies the sensor data and navigation instructions to the machine learning model to generate a set of audio navigation instructions responsive to the request.

Abstract: Techniques are described herein for concurrent voice assistants. A method includes: providing first and second automated assistants with access to one or more microphones; receiving, from the first automated assistant, an indication that the first automated assistant has initiated a first session, and in response: continuing providing, to the first automated assistant, access to the one or more microphones; discontinuing providing, to the second automated assistant, access to the one or more microphones; and preventing the second automated assistant from accessing one or more portions of an output audio data stream; receiving, from the first automated assistant, an indication that the first session has ended, and in response: continuing providing, to the first automated assistant, access to the one or more microphones; resuming providing, to the second automated assistant, access to the one or more microphones; and resuming providing, to the second automated assistant, the output audio data stream.